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Augusto Becerra Lopez-Lavalle, Claudia Perea, Margit Drapal and Paul Fraser
The Application of Genomics and Metabolomics to the assessment of biodiversity in Cassava 20th of January 2016 Nanning, China
E-mail [email protected]
Transcriptional control
Post-translational modification
Translational control
Genetic/epigenetic control
Enzyme regulation
Metabolite regulation
Genomic differences are associated with different biochemical and cellular regulation mechanisms that define TRAITS
Trait/phenotype
Genomics
Phenomics
Nucleic acids
Proteins/ peptides
Small molecules
Proteomics
Metabolomics
Transcriptional control
Post-translational modification
Translational control
Genetic/epigenetic control
Enzyme regulation
Metabolite regulation
Genomic differences are associated with different biochemical and cellular regulation mechanisms that define TRAITS
Trait/phenotype
Genomics
Phenomics
Nucleic acids
Proteins/ peptides
Small molecules
Proteomics
Metabolomics
Cassava in the Post Genomic Era
Cassava in the Post Genomic Era
2012
2013
Exploiting Intra and Inter specific variation
CIAT’s keeps the crops’ largest gene diversity
5,264 M. esculenta Landraces clones 883 wild species genotypes 435 M. esculenta Elite CIAT clones 600 Core collection
Cassava production
Sampling
109 Cassava Landraces exploited for breeding in the past 40 years
COL22
COL1684
COL1505 AM560-2
S3
Sampling
109 Cassava Landraces exploited for breeding in the past 40 years
COL22
COL1684
COL1505 AM560-2
S3
355 Samples
6% of the CIAT collection 45 core materials
Bioinformatics Pipeline for variants detection
Population Structure
Variants Detection 8455 Biallelic SNPs
Mapping
Raw RAD-seq
Reads Reference
Genome vs.6.1
Population Genomics GWAS
AM560-2
Bowtie Vs2.2.5 NGSEP Vs.2.1.1
Structure TreeMix Tassel MLM
Illumina Paired-end
reads 83% average (75-86%)
Eco-geographic signature of the crop’s domestication patterns
K2
Approximately 12,127 high quality SNPs
Eco-geographic signature of the crop’s domestication patterns
NORTH
SOUTH
Eco-geographic signature of the crop’s domestication patterns
K7
Approximately 12,127 high quality SNPs
K7
Eco-geographic signature of the crop’s domestication patterns
CARIBEAN SAVANNA
ANDEAN
HUMID ATLANTIC FOREST
DRY ATLANTIC FOREST
AMAZON
Eco-geographic signature of the crop’s domestication patterns
M. flabellifolia M. peruviana M. tristis
LD decay
Number of Samples
LD decay (Kbp)
Cassava 355 10 AND 71 15 ARB 30 24 SARF 60 25 HAF 52 29 DAF 55 29 SAV 36 45 MAC 51 46
Eco-geographic signature of the crop’s domestication patterns
M. flabellifolia M. peruviana M. tristis
LD decay
Number of Samples
LD decay (Kbp)
Cassava 355 10 AND 71 15 ARB 30 24 SARF 60 25 HAF 52 29 DAF 55 29 SAV 36 45 MAC 51 46
7 Kbp
Manihot genus & putative ancestor of the domesticated form
Manihot genus & putative ancestor of the domesticated form
Range of Expansion
Manihot genus & putative ancestor of the domesticated form
Range Expansion Analysis
Loren Reiseberg’s Lab
Manihot genus & putative ancestor of the domesticated form
Range Expansion Analysis
Loren Reiseberg’s Lab
Applications for impact 180 SNPs
Variety identification
Applications for impact
Applications for impact
Variety identification
Role of Metabolomics/metabolite profiling in Crop Improvement
Type of metabolomic/metabolite profiling technologies
Type of metabolomic/metabolite profiling technologies
PHASE-I
The contribution to cassava and other RTBs
• Assessing biodiversity. • Systems (integrative) approaches to gene and allele mining. • Trait discovery- large scale (genome-wide) metabolomic
screening of diversity populations. • Characterisation of varieties/products- elucidating underlying
biochemical and molecular mechanisms associated with traits.
• Adaption to climate change/abiotic/biotic stresses.
Diversity panel In vitro cassava plantlets Sender Code Characteristic trait Sender
Code Characteristic trait
BRA1A High carotene ECU72 WF Resistance/Bacteriosis Susceptible
BRA488 High Cyanide Content GUA35 Low Sugar Content
COL113 PAN139 Trips Resistance
COL1505 Z01 and Z04 adaptation PAR36 High Amylose Content
COL1684 Z03 adaptation PER 496 HGCA
COL2017 High Sugar Content PER183 High PPD Tolerance/Frog Skin disease/Low Carotene
COL22 PPD susceptible TME3 CMD
COL2436 High Carotene/Trips Susceptible TMS30555 CMD
COL638 Bacteriosis resistance TMS60444 Transformation
CUB23 Low Amylose Content VEN25 Low Culinary Quality
CUB25 Low Amylose Content VEN77 Drought tolerance
CUB74 High Culinary Quality/Z06 adaptation
Field samples analysed Material: leaf, stem and tuberous root
Metabolomics Workflow of analysis
10 mg
> 9000 Chemical features
Sam
ples
run
(QCs
, re
ps, e
tc.)
Untargeted analysis (LC-MS) of in vitro prepared plantlets
LC-MS (TIC)
10mg Freeze-dried
material
A genome-wide metabolomic resource for tomato fruit from Solanum pennellii Laura Perez-Fons1, Tom Wells1, Delia I. Corol2, Jane L. Ward2, Christopher Gerrish1, Michael H. Beale2, Graham B. Seymour3, Peter M. Bramley1 & Paul D. Fraser1
1Centre for Systems and Synthetic Biology, School Biological Sciences, Royal Holloway
SCIENTIFIC REPORTS | 4 : 3859 | DOI: 10.1038/srep03859
• 20,309 statistically significant measured variable changes. • Health traits 1,474 increase and 1,346 decrease mQTL .
•2000 compounds putatively identified and placed into 500 PlantCyc pathways.
BRA_1A
BRA_488
COL_113
COL_1505
COL_1684
COL_2017
COL_22
COL_2436
COL_638
CUB_23
CUB_25
CUB_74
ECU_72
GUA_35
PAN_139
PAR_36
PER_496
PER_183
TME_3
TMS_30555
TMS_60444
VEN_25
VEN_77
(31.9%)
(11%
)
PCA of untargeted analysis (LC-MS) of in vitro prepared plantlets
Africa Central America and Caribbean South America
• Two independent experiments - average six biological replicates 10mgFD material
Summary
The variation in biochemical composition (in vitro) separates on: • Consumer traits v
biotic/abiotic tolerance • Intermediary and secondary
metabolites • Genotype/geographical
origin
Organic acids Amino acids Fatty acids, sugars and
saccharides Terpenoids
GC-MS chromatograms of Cassava polar/non-polar extracts
BRA 1A
BRA 488
COL 113
COL 1505 COL 1684COL 2017 COL 22
COL 2436
COL 638
CUB 23
CUB 25 CUB 74ECU 72
GUA 35
PAN 139
PAR 36
PER 183
PER 496
TME 3
TMS 30555
TMS 60444VEN 25
VEN 77
(25.6%)
(14.
2%)
Phenylpropanoids
Linamarin
Africa Central America and Caribbean South America
Intermediary metabolites
PCA targeted analysis (LC-MS, GC-MS & UPLC-PDA) of in vitro prepared plantlets
25 diverse accessions in the field at CIAT
BRA1A
COL22
COL638
CUB23PER183
BRA1A
COL22
COL638
CUB23PER183
BRA1ACOL22
COL638CUB23
PER183
(46.5%)
(28.
6%)
Metabolite profiling of accessions and their tissues generated by cultivation in the field
Leaf
Root
Stem
PCA applied to metabolite profiles from five accessions grown under field conditions
Stem
Leaf
Root
BRA1ACOL22
COL638
CUB23
PER183
(44.9%)
(24.
5%)
Amino acids
PCA applied to metabolite profiles of leaf material from five accessions grown under in vitro and field conditions
BRA1A
COL22
COL638
CUB23PER183
(39.8%)
(29.
1%)
Intermediary metabolites and pigments
Sugars/ carbohydrate
Amino acids
Sugars/ carbohydrate
Intermediary metabolites and pigments
In vitro plants Field plants
• Robust metabolomics platforms established. • Initial networks of the Cassava metabolome in
place. • In vitro cultivation is a good representation of
field generated material. • Genetic/biochemical effects overcome
environmental effects. • The range of diversity similar across RTB crops. • A Cassava resource and toolkit generated to
enabling the elucidation of underlying biochemical changes associated with traits of interest.
Conclusions and Future
Germplasm Bank CIAT Daniel Debouck, Ericsson Aranzales
Cassava Molecular Genetics Lab Tatiana Ovalle, Katherine Castillo, and Adriana Alzate
CIAT’s bioinformatics team Jorge Duitama
External Colaborators Sequencing
Beijing Genomics Institute- BGI Metabolomics
Fraser’s Lab at RHUL Margit Drapal
Funding: CIAT - RTB partnership
Acknowledgments CIAT’s Cassava Program
Joe Tohme, Clair Hershey, Hernan Ceballos
THANK YOU FOR YOUR ATTENTION